A typical industrial manufacturing plant involves a number of processes which produce products. Each process consists of a number of sub-processes. A primary goal of plant management is to operate the plant as efficiently (as close to optimum performance) as possible to give the lowest product cost. However, it is not unusual for a plant to operate less than optimally. This may happen for a variety of reasons. Difficulties may be caused by one or more problems in the process or sub-processes. For example, a power failure may stop all processes. A jam in a cap chute in a bottling plant may cause un-capped bottles which may require an extra operator to cap the bottles manually. In today's complex manufacturing plants, there may be thousands of separate problems which cause performance to deviate from optimum levels. Since resources for fixing such problems are not unlimited, management is often faced with difficult choices as to which problems to solve and the order in which they should be solved.
Using the technology of the prior art, it was possible to track the performance of an industrial process by means of the following:
1. calculating the efficiency of the process (i.e. the ratio of the actual output to the true potential output); PA1 2. determining reasons for downtime (i.e. the identity and duration of the problems that stop the bottleneck); PA1 3. determining labor variance (i.e. the difference between the actual direct labor cost and budgeted or planned direct labor cost); PA1 4. determining raw material variance (i.e. the difference between the actual raw material consumption and budgeted or planned raw material consumption); and PA1 5. determining the scrap level (i.e. the amount of product rejected during or upon completion of the manufacturing process).
Each of these approaches has deficiencies. In particular, none of the approaches of the prior art attempts to calculate the true financial cost of an individual problem nor the total cost of all problems affecting an industrial process. It is therefore impossible for plant management to allocate resources in an efficient manner if prior art approaches are employed.
The present invention addresses these and other numerous deficiencies of the prior art.